• 제목/요약/키워드: Ill-conditioned singular linear system

검색결과 4건 처리시간 0.026초

ILL-VERSUS WELL-POSED SINGULAR LINEAR SYSTEMS: SCOPE OF RANDOMIZED ALGORITHMS

  • Sen, S.K.;Agarwal, Ravi P.;Shaykhian, Gholam Ali
    • Journal of applied mathematics & informatics
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    • 제27권3_4호
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    • pp.621-638
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    • 2009
  • The linear system Ax = b will have (i) no solution, (ii) only one non-trivial (trivial) solution, or (iii) infinity of solutions. Our focus will be on cases (ii) and (iii). The mathematical models of many real-world problems give rise to (a) ill-conditioned linear systems, (b) singular linear systems (A is singular with all its linearly independent rows are sufficiently linearly independent), or (c) ill-conditioned singular linear systems (A is singular with some or all of its strictly linearly independent rows are near-linearly dependent). This article highlights the scope and need of a randomized algorithm for ill-conditioned/singular systems when a reasonably narrow domain of a solution vector is specified. Further, it stresses that with the increasing computing power, the importance of randomized algorithms is also increasing. It also points out that, for many optimization linear/nonlinear problems, randomized algorithms are increasingly dominating the deterministic approaches and, for some problems such as the traveling salesman problem, randomized algorithms are the only alternatives.

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비최소 위상을 갖는 외팔보에서 SVD를 이용한 역변환 문제에 관한 연구 (A Study on the Application of SVD to an Inverse Problem in a Cantilever Beam with a Non-minimum Phase)

  • 이상권;노경래;박진호
    • 한국소음진동공학회논문집
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    • 제11권9호
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    • pp.431-438
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    • 2001
  • This paper present experimental results of source identification for non-minimum phase system. Generally, a causal linear system may be described by matrix form. The inverse problem is considered as a matrix inversion. Direct inverse method can\`t be applied for a non-minimum phase system, the reason is that the system has ill-conditioning. Therefore, in this study to execute an effective inversion, SVD inverse technique is introduced. In a Non-minimum phase system, its system matrix may be singular or near-singular and has one more very small singular values. These very small singular values have information about a phase of the system and ill-conditioning. Using this property we could solve the ill-conditioned problem of the system and then verified it for the practical system(cantilever beam). The experimental results show that SVD inverse technique works well for non-minimum phase system.

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Prediction of propagated wave profiles based on point measurement

  • Lee, Sang-Beom;Choi, Young-Myoung;Do, Jitae;Kwon, Sun-Hong
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제6권1호
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    • pp.175-185
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    • 2014
  • This study presents the prediction of propagated wave profiles using the wave information at a fixed point. The fixed points can be fixed in either space or time. Wave information based on the linear wave theory can be expressed by Fredholm integral equation of the first kinds. The discretized matrix equation is usually an ill-conditioned system. Tikhonov regularization was applied to the ill-conditioned system to overcome instability of the system. The regularization parameter is calculated by using the L-curve method. The numerical results are compared with the experimental results. The analysis of the numerical computation shows that the Tikhonov regularization method is useful.

역 문제에 의한 파이프의 결함위치 평가 (Estimation of Defect Position on the Pipe Line by Inverse Problem)

  • 박성완
    • 한국생산제조학회지
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    • 제20권2호
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    • pp.139-144
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    • 2011
  • This paper presents a boundary element application to determine the optimal impressed current densities at defect position on the pipe line. In this protection paint, enough current must be impressed to lower the potential distribution on the metal surface to the critical values. The optimal impressed current densities are determined in order to minimize the power supply for protection. This inverse problem was formulated by employing the boundary element method. Since the system of linear equations obtained was ill-conditioned, including singular value decomposition, conjugate gradient method were applied and the accuracies of these estimation. Several numerical examples are presented to demonstrate the practical applicability of the proposed method.